Stock Returns’ Co-Movement: A Spatial Model with Convex Combination of Connectivity Matrices

Nadia Ben Abdallah, Halim Dabbou (), Mohamed Imen Gallali and Salem Hathroubi
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Nadia Ben Abdallah: Department of Finance, Higher Institute of Management, University of Sousse, Sousse BN1 9RH, Tunisia
Halim Dabbou: Department of Administration, Hearst University, Campus of Timmins, Timmins, ON P0L 1N0, Canada
Mohamed Imen Gallali: Laboratory of Research in Innovative Management, Risk, Accounting and Finance, University of Manouba, Manouba LR21ES29, Tunisia
Salem Hathroubi: Department of Economics, College of Business, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh 11564, Saudi Arabia

Risks, 2025, vol. 13, issue 6, 1-19

Abstract: This paper examines the extent of stock-returns’ co-movements among firms in different countries and explores how various measures of closeness affect those co-movements by estimating a spatial autoregressive (SAR) convex combination model that merges four weight matrices—geographical distance, bilateral trade, sector similarity, and company size—into one global matrix. Our results reveal strong spatial stock-market dependence, show that spatial proximity is better captured by financial-distance measures than by pure geographical distance, and indicate that the weight matrix based on sector similarities outperforms the other linkages in explaining firms’ co-movements. Extending the traditional SAR model, the study simultaneously evaluated cross-country and within-country dependencies, providing insights valuable to investors building optimal portfolios and to policymakers monitoring contagion and systemic risk.

Keywords: stock market co-movements; spatial econometrics; the SAR convex combination model (search for similar items in EconPapers)
JEL-codes: C G0 G1 G2 G3 K2 M2 M4 (search for similar items in EconPapers)
Date: 2025
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